Search Results (3,082)

The retention of organizational knowledge is increasingly challenging for companies giventhe aging workforce, high turnover rates, and declining birth rates. This study explores the knowledge transfer processes during generational transitions and examines how digital transformation facilitates business model innovation. Specifically, it examines theknowledge transfer procedures implemented in companies in the Autonomous Community of the Basque Country, a competitive industrial region in Europe. Using a quantitative approach, 168 individuals in key leadership positions were surveyed on the mechanisms used for knowledge retention and their effectiveness. The results reveal that while companies prioritize knowledge transfer, most lack effective protocols. Organizations employing both digital and analog strategies are perceived as more efficient in retaining knowledge. Only half of the companies integrate knowledge transfer processes into their management strategies, with no observed differences in employee knowledge-sharing behaviors based on company size. This study concludes that a lack of structured procedures may harm long-term competitiveness, recommending that companies invest more in developing formal generational handover protocols. This research underscores the vital importance of knowledge retention for organizational sustainability and highlights the need for further exploration to address this issue. Full article

A 3-year-old, 10.2 kg, spayed, female mixed-breed dog was diagnosed with systemic lupus erythematosus. The patient was administered intravenous methylprednisolone at a dose of 2 mg/kg twice daily. Over the next 24 h, the dog’s heart rate dropped to 42–48 bpm, while other vital signs remained stable. A 12-lead electrocardiogram revealed sinus bradycardia without any other arrhythmia. Notably, the dog was not receiving any beta-blockers or undergoing other therapies commonly associated with sinus bradycardia. After tapering the corticosteroid dose, no further episodes of bradycardia were observed. Herein, we report the first case of sinus bradycardia in a dog following intravenous methylprednisolone therapy to improve veterinarians’ understanding of corticosteroid-induced cardiac arrhythmias. Full article

Mangroves play a crucial role in supporting the biodiversity of coastal wetlands, acting as a vital link between terrestrial and marine ecosystems. In mainland China, Sonneratia apetala, an invasive mangrove species, has recently become dominant in these environments. While it contributes to the stability of mangrove ecosystems and is widely used in coastal restoration efforts, its rapid growth poses a significant threat to the survival of native mangrove species. However, the spatiotemporal growth dynamics and landscape impacts of Sonneratia apetala remain underexplored in scholarly research. This study employs remote sensing and GIS techniques to analyze the growth patterns of Sonneratia apetala over a 14-year period along the eastern coast of the Leizhou Peninsula in China. The analysis revealed the following key findings: (1) The mangrove area expanded from 274.17 hm² to 383.42 hm², with an average annual growth rate of 2.84%. (2) The area of Sonneratia apetala increased from 115.15 hm² in 2010 to 254.81 hm² in 2023, with an average annual growth rate of 1.29%. The area of local mangrove species declined from 163.02 hm² to 125.06 hm² (a decrease from 22.11% to 16.96%), with an average annual growth rate of −1.66%. (3) The number of Sonneratia apetala patches increased from 139 to 324, while the area-weighted shape index rose from 3.4 to 7.81. The decline of native mangrove species, driven by the rapid spread of Sonneratia apetala, suggests that this species is encroaching on native mangrove habitats. Through geospatial analysis, this study provides valuable insights into how introduced species can reshape mangrove landscape structures and the broader implications for regional biodiversity. These findings clearly demonstrate that Sonneratia apetala is encroaching upon local mangrove habitats, highlighting the urgent need for strategic management and conservation efforts to mitigate the ecological impacts of the proliferation of this species. Furthermore, this research is important for coastal sustainability management strategies that balance ecological restoration with the preservation of native biodiversity, ensuring long-term ecosystem health and resilience. Full article

Background: Preterm infants often have unstable vital signs and prolonged hospital stays that can hinder parent–infant bonding, especially under COVID-19 restrictions. This study aimed to evaluate whether listening to songs recorded by parents was effective in stabilizing the condition of premature infants. Methods: This randomized controlled study was conducted at the University of Miyazaki Hospital from October 2022 to March 2024 during the COVID-19 pandemic period. The participants were preterm infants born at less than 33 weeks gestation and their parents, all of whom recorded songs. The recorded songs were played daily to the infants in the intervention group, while the control group received usual care. Primary outcomes included vital signs (respiratory rate, pulse oximetry saturation, heart rate) and activity level. Results: Data for 33 preterm infants (intervention, n = 17 [total 749 sessions]; control, n = 16 [total 721 sessions]) were analyzed for changes in vital signs and activity levels. The intervention reduced infants’ respiratory rates (4.1 [95% CI: 2.5–5.6], p < 0.001) and slightly but statistically significantly increased pulse oximetry saturation (0.6 [95% CI: 0.02–1.2], p < 0.044). Conclusions: Recorded parental songs were found to safely stabilize the respiratory status of preterm infants and may serve as an accessible intervention to support parent–infant attachment, particularly in settings with restricted parental visitation. Full article

Titanium alloys find extensive applications in aviation, maritime, and chemical engineering applications. Nonetheless, these alloys encounter significant challenges during the conventional forging process, which include high deformation resistance, limited processing temperature ranges, and inhomogeneous microstructure. Isothermal forging, as a near-net-shape forming technique, can alleviate the microstructural inhomogeneity caused by deformation dead zones in conventional forging, thus enabling the direct production of complex shapes. This process enhances the overall performance and utilization of materials while reducing manufacturing costs. This paper comprehensively reviews how isothermal near-net-shape forging process parameters influence the intricate microstructure and essential properties of titanium alloys. The unique properties of isothermal forging applied to high-performance titanium alloys are also discussed in depth, and the intricate interplay between process parameters and the microstructure and properties of recoloration is clarified. That is to say, temperature is a vital element influencing the phases and microstructure of titanium alloys during the forming process. Grain size, microstructural homogeneity, and phase transformation are influenced by the strain rate, thereby affecting the plasticity, fracture toughness, and strength of titanium alloys. The extent of deformation significantly governs the grain size, the thickness of secondary α phase, dynamic recrystallization, and primary α phase. Cooling rate affects the grain size and precipitates, contributing to grain refinement. The frequency of isothermal forging affects the grain refinement and microstructural uniformity of titanium alloys. Finally, this paper summarizes the scientific questions that remain unresolved in this field and outlines future research directions to promote the further development of isothermal near-net-shape forging processes and facilitate the broader industrial applications of high-performance titanium alloys and other difficult-to-form alloys. Full article

Monitoring physiological parameters is vital for tracking swimmers’ progress and performance. This study examines an elite male swimmer’s nutrition during his preparation for the 2024 Paris Olympics, considering his metabolic rate and body composition. His resting energy needs (2905 ± 407.99 kcal/day) were measured using indirect Cosmed K5, calorimetry, and body composition determined through skinfold measurements. Nutrition plans were developed using software, varying with his training intensity—providing 2910 ± 379 kcal/day on rest days, and 4238 ± 562 kcal/day on intense days. The analysis of the correlations between key variables revealed strong and diverse interactions among anthropometric, metabolic data, and energy substrates. Thus, weight exhibited a very strong positive correlation with lean mass (FFM), indicating that higher weight is associated with increased lean mass. Conversely, the moderate correlation between weight and body fat percentage suggests a weaker association. The amount of skin folds accurately reflects the body fat percentage. Ensuring that a high-energy dietary intake aligned with his actual needs throughout the season was crucial for sustaining performance. Experimenting with fueling and recovery tactics during smaller competitions enabled the athlete to meet energy and nutrient demands at the elite level. Full article

Background/Objectives: Children who suffer from congenital heart defects (CHDs) have a decreased ability to perform physical exercise and consequently have a decrease in their functional capacity. The main causes of this decrease in functional capacity have been related on the one hand to residual hemodynamic defects and, at the same time, to a situation of physical deconditioning due to inactivity, as well as problems in lung function, especially the presence of restrictive patterns that influence the amount of O₂ insufflated (decreased maximum VO₂), consequently generating a deficient maximum O₂ consumption and maximum work rate. This represents an important prognostic value, since it constitutes an independent predictor of death and hospitalization. This study aims to determine the benefits obtained regarding respiratory function, exercise capacity, and quality of life after implementing a hospital-based cardio-respiratory rehabilitation program compared to a home-based Cardio-respiratory Physical Activity Program in patients with intervened CHDs. Methods: This is a randomized controlled trial on the effectiveness of two different rehabilitation programs on respiratory function, exercise capacity, and quality of life in patients with CHDs conducted at the Child Cardiology and Congenital Heart Disease Unit of the University Hospital Complex of A Coruña (CHUAC). There will be two groups: Cardio-respiratory rehabilitation group program conducted in a face-to-face format at the hospital (n = 26) and a study group that follows a home-based Cardio-respiratory Physical Activity Program (TELEA) (n = 26). The measurement variables will be respiratory function, forced vital capacity (FVC), forced expiratory volume in the first second (FEV1), maximum expiratory flow (PEF), the Tiffeneau index (FEV1 /FVC), forced expiratory flow (FEF25%, FEF50%, FEF75%, FEF25–75%), exercise capacity (peak VO₂), and the quality of life of these children and their families. Conclusions: The implementation of cardiac and pulmonary rehabilitation programs in children with CHDs is essential to improve their quality of life, exercise tolerance, and socialization. These programs optimize life expectancy and promote integration, being crucial for their physical and emotional well-being Full article

Accurate flow stress prediction is vital for optimizing the manufacturing of lightweight materials under high-temperature conditions. In this study, a boron nitride (BN)-reinforced AZ80 magnesium composite was subjected to hot compression tests at temperatures of 300–400 °C and strain rates ranging from 0.01 to 10 s⁻¹. A data-driven Support Vector Regression (SVR) model was developed to predict flow stress based on temperature, strain rate, and strain. Trained on experimental data, the SVR model demonstrated high predictive accuracy, as evidenced by a low mean squared error (MSE), a coefficient of determination (R²) close to unity, and a minimal average absolute relative error (AARE). Sensitivity analysis revealed that strain rate and temperature exerted the greatest influence on flow stress. By integrating machine learning with experimental observations, this framework enables efficient optimization of thermal deformation, supporting data-driven decision-making in forming processes. The results underscore the potential of combining advanced computational models with real-time experimental data to enhance manufacturing efficiency and improve process control in next-generation lightweight alloys. Full article

Dust storms, characterized by their rapid movement and high intensity, present significant challenges across atmospheric, human health, and ecological domains. This study investigates the spatiotemporal variations in dust intensity (DI) and its driving factors in Mongolia from 2001 to 2022, using data from ground observations, reanalysis, remote sensing satellites, and statistical analyses. Our findings show an increasing DI trend at approximately two-thirds of the monitoring stations, with DI rising at an average rate of 0.8 per year during the study period. Anthropogenic factors dominate as the primary drivers in regions such as Forest, Meadow Steppe, Typical Steppe, Desert Steppe, and the Gobi Desert. For example, GDP significantly impacts Forest and Meadow Steppe areas, contributing 25.89% and 14.11% to influencing factors of DI, respectively. Population emerges as the key driver in Typical Grasslands (20.77%), Desert Steppe (26.65%), and the Gobi Desert (37.66%). Conversely, climate change is the dominant factor in the Alpine Meadow regions of southern–central Hangay Uul, with temperature (20.69%) and relative humidity (20.67%) playing critical roles. These insights are vital for Mongolian authorities: promoting green economic initiatives could mitigate DI in economically active Desert Steppe regions, while climate adaptation strategies are essential for climate-sensitive Alpine Meadows. The findings also provide valuable guidance for addressing environmental issues in other arid and semi-arid regions worldwide. Full article

Wind turbines are predominantly situated in remote, high-altitude regions, where they face a myriad of harsh environmental conditions. Factors such as high humidity, strong gusts, lightning strikes, and heavy snowfall significantly increase the vulnerability of turbine blades to fatigue damage. This susceptibility poses serious risks to the normal operation and longevity of the turbines, necessitating effective monitoring and maintenance strategies. In response to these challenges, this paper proposes a novel fault detection method specifically designed for analyzing wind turbine blade noise signals. This method integrates the Tyrannosaurus Optimization Algorithm (TROA) with a support vector machine (SVM), aiming to enhance the accuracy and reliability of fault detection. The process begins with the careful preprocessing of raw noise signals collected from wind turbines during actual operational conditions. The method extracts vital features from three key perspectives: the time domain, frequency domain, and cepstral domain. By constructing a comprehensive feature matrix that encapsulates multi-dimensional characteristics, the approach ensures that all relevant information is captured. Rigorous analysis and feature selection are subsequently conducted to eliminate redundant data, thereby focusing on retaining the most significant features for classification. A TROA-SVM classification model is then developed to effectively identify the faults of the turbine blades. The performance of this method is validated through extensive experiments, which indicate that the recognition accuracy rate is 98.7%. This accuracy is higher than that of the traditional methods, such as SVM, K-Nearest Neighbors (KNN), and random forest, demonstrating the proposed method’s superiority and effectiveness. Full article

Groundwater in northwest Tunisia plays a vital role in supporting the domestic, agriculture, industry, and tourism sectors. However, climate change and over-exploitation have led to significant degradation in groundwater quality and quantity. Traditional spatial analysis techniques such as Geographic Information Systems (GIS) and Remote Sensing (RS) are frequently used for assessing groundwater potential and water quality. Yet, these methods are limited by data availability. The integration of Geospatial Artificial Intelligence (Geo-AI) offers improved precision in groundwater potential zone (GWPZ) delineation. This study compares the effectiveness of the Analytical Hierarchy Process (AHP) and advanced Geo-AI techniques using deep learning to map GWPZ in the Majerda transboundary basin, shared between Tunisia and Algeria. By incorporating thematic layers such as rainfall, slope, drainage density, land use/land cover (LU/LC), lithology, and soil, a comprehensive analysis was conducted to assess groundwater recharge potential. The results revealed that both methods effectively delineated GWPZ; however, the Geo-AI approach demonstrated superior accuracy with a classification accuracy rate of approximately 92%, compared to 85% for the AHP method. This indicates that Geo-AI not only enhances the quality of groundwater potential assessments but also offers a reliable alternative to traditional methods. The findings underscore the importance of adopting innovative technologies in groundwater exploration efforts in this critical region, ultimately contributing to more effective and sustainable water resource management strategies. Full article

Cropland serves as the most vital resource for agricultural production, while its security is primarily threatened by abandonment. Northeast Guangdong Province features a fragmented terrain and faces a significant issue of farmland abandonment. It is crucial to analyze the phenomenon of cropland abandonment to safeguard food security. However, due to limitations in data sources and attribution methods, previous studies struggled to comprehensively characterize the driving mechanisms of abandoned land. Using data from Sentinel time series remote-sensing images, we employed the land use change trajectory method to map cropland abandonment in Jiaoling County from 2019 to 2023. Furthermore, we proposed a novel analytical framework to quantify the influence pathways and interaction effects driving cropland abandonment. The results indicated that: (1) The overall accuracy of the abandoned land extraction was 79.6%. During the study period, the abandonment rate in Jiaoling County showed a trend of a “gradual rise followed by a sharp decline”, and the abandoned area reached its maximum in 2021. The abandonment phenomenon in the southeastern rural areas was serious and stubborn. (2) The slope has the greatest explanatory power for abandonment, followed by the total cultivated area, aggregation index of cropland, and distance to road. Each driving factor has a threshold effect. (3) Topography, location, and agriculture driving factors directly or indirectly affect the abandonment rate, with direct influences of 0.247, 0.255, and −0.256, respectively. The research findings offer valuable scientific guidance for managing abandoned land and deepen our understanding of its formation mechanisms. Full article

Cucumber, a vital greenhouse crop, thrives in soils with a pH range of 5.5–6.5, yet the combined effects of arbuscular mycorrhizal fungi (AMF) and iron amino chelates on its growth and physiological responses across varying pH levels remain underexplored. This study used a factorial design in a completely randomized setup with three replications and was conducted at the Horticulture Department of Isfahan University of Technology. The aim of this study was to investigate the effects of AMF inoculation (Glomus mosseae) and iron amino chelates on the growth and physiological responses of cucumber plants at various pH levels. Treatments included two levels of AMF inoculation (non-inoculated as m1 and inoculated as m²), three levels of iron concentration (f1: no iron, f2: Johnson’s nutrient solution, f3: Johnson’s solution with iron amino chelate), and three pH levels (pH 5 (p1), pH 7 (p2), and pH 8 (p3)). The moisture was maintained at field capacity throughout the study. The results demonstrated that mycorrhizal inoculation at pH 7 significantly improved key traits, including chlorophyll content, photosynthesis rate, stomatal conductance, phenol content, and antioxidant activity. Mycorrhizal inoculation combined with 2 ppm of Fe amino chelate at pH 7 led to the highest improvement in shoot fresh weight of cucumber and physiological traits. However, at pH 7 without mycorrhiza, stress indicators such as ABA levels and antioxidant enzyme activities (SOD, POD, CAT, and APX) increased, highlighting the protective role of AMF under neutral pH conditions. In contrast, pH 5 was most effective for enhancing root and stem fresh weight. The lower pH may have facilitated better nutrient solubility and uptake, promoting root development and overall plant health by optimizing the availability of essential nutrients and reducing competition for resources under more acidic conditions. These findings highlight the potential of combining mycorrhizal inoculation with iron amino chelates at pH 7 not only to enhance cucumber growth and resilience in nutrient-limited environments but also to contribute to sustainable agricultural practices that address global challenges in food security and soil health. Full article

As the scale of real estate project financing (PF) of large construction companies in South Korea increase, discontinued construction projects and PF default rates in the financial world are also rapidly increasing. Furthermore, the percentage of PF bad debts in South Korea today has increased as much as about three times compared to that in 2023. The increase in bad debt rates results mainly from the moderate supply of new funds, delays in non-performing PF arrangements, and so forth. To address this problem, it is necessary to restart the development of non-performing real estate PF development sites through successful bidding and to review the valuation basis for development projects. Therefore, this study aims to derive internal and external characteristics of non-performing real estate PF development sites in South Korea and examine the effects of specific factors on their successful bidding. In addition, significant variables are selected based on the analysis result; the analytic hierarchy process (AHP) analysis is performed to establish a new valuation system for real estate development projects. After careful consideration of various literature reviews and expert opinions, an analysis model is established to ensure the suitability of the study model with the error range minimized. As AHP was performed based on the newly established hierarchy, the higher ranks of each valuation factor were derived based on priority and importance, and the valuation basis was rearranged accordingly. The conclusion was derived through a comprehensive review of the results of the two analyses above. It was verified that certain factors—business feasibility assessment, work performance assessment, and basic evaluation—played key roles in the success and successful bidding of real estate projects. This point suggests that strict project management and performance standards must be set based on the economic achievements of financial validity indexes and business performance capabilities. Stable profit distribution and business transparency are also viewed as vital factors for the success of projects. Therefore, this study reestablishes the valuation basis for development projects in South Korea and presents policy suggestions on location propriety and business advancement based on the analysis of non-performing PF bid decision factors and the development project valuation basis. Full article

Loblolly pine plantations have long been cultivated primarily for timber production due to their rapid growth and economic value. However, these forests are now increasingly acknowledged for their important role in mitigating climate change. Their dense canopies and fast growth rates enable them to absorb and store substantial amounts of atmospheric carbon dioxide. By integrating sustainable management practices, these plantations can maximize both timber yield and carbon sequestration, contributing to global efforts to reduce greenhouse gas emissions. Balancing timber production with vital ecosystem services, such as carbon storage, demands carefully tailored management strategies. This study examined how the timing of thinning—specifically early thinning at 17 years and late thinning at 32 years—impacts biomass accumulation, carbon storage capacity, and carbon sequestration rates in loblolly pine plantations located in northern Iran. Two thinning intensities were evaluated: normal thinning (removal of 15% basal area) and heavy thinning (removal of 35% basal area). The results demonstrated that thinning significantly improved biomass, sequestration rates and carbon storage compared to unthinned stands. Early thinning proved more effective than late thinning in enhancing these metrics. Additionally, heavy thinning had a greater impact than normal thinning on increasing biomass, carbon storage, and sequestration rates. In early heavy-thinned stands, carbon storage reached 95.8 Mg C/ha, which was 63.0% higher than the 58.8 Mg C/ha observed in unthinned 32-year-old stands. In comparison, early normal thinning increased carbon storage by 41.3%. In late heavy-thinned stands, carbon storage reached 199.4 Mg C/ha, which was 29.0% higher than in unthinned stands of the same age (154.6 Mg C/ha at 52 years). In contrast, late normal thinning increased carbon storage by 13.3%. Similarly, carbon sequestration rates in unthinned stands were 1.84 Mg C/ha/yr at 32 years and 2.97 Mg C/ha/yr at 52 years. In comparison, 32-year-old stands subjected to normal and heavy thinning had sequestration rates of 2.60 and 2.99 Mg C/ha/yr, respectively, while 54-year-old normally and heavily thinned stands reached 3.37 and 3.83 Mg C/ha/yr, respectively. The highest carbon storage was concentrated in the stems for 52–58% of the total. Greater thinning intensity increased the proportion of carbon stored in stems while decreasing the contribution from foliage. These results indicate that heavy early thinning is the most effective strategy for maximizing both timber production and carbon sequestration in loblolly pine plantations. Full article